[HTML][HTML] A survey on network data collection
D Zhou, Z Yan, Y Fu, Z Yao - Journal of Network and Computer …, 2018 - Elsevier
Networks have dramatically changed our daily life and infiltrated all aspects of human
society. At the same time when we enjoy the convenience and benefits brought by the …
society. At the same time when we enjoy the convenience and benefits brought by the …
A tutorial on variable selection for clinical prediction models: feature selection methods in data mining could improve the results
F Bagherzadeh-Khiabani, A Ramezankhani… - Journal of clinical …, 2016 - Elsevier
Objectives Identifying an appropriate set of predictors for the outcome of interest is a major
challenge in clinical prediction research. The aim of this study was to show the application of …
challenge in clinical prediction research. The aim of this study was to show the application of …
Pearson correlation-based feature selection for document classification using balanced training
Documents are stored in a digital form across several organizations. Printing this amount of
data and placing it into folders instead of storing digitally is against the practical, economical …
data and placing it into folders instead of storing digitally is against the practical, economical …
Famd: A fast multifeature android malware detection framework, design, and implementation
H Bai, N ** a multi-dose computational model for drug-induced hepatotoxicity prediction based on toxicogenomics data
Drug-induced hepatotoxicity may cause acute and chronic liver disease, leading to great
concern for patient safety. It is also one of the main reasons for drug withdrawal from the …
concern for patient safety. It is also one of the main reasons for drug withdrawal from the …
A survey on feature selection techniques based on filtering methods for cyber attack detection
Y Lyu, Y Feng, K Sakurai - Information, 2023 - mdpi.com
Cyber attack detection technology plays a vital role today, since cyber attacks have been
causing great harm and loss to organizations and individuals. Feature selection is a …
causing great harm and loss to organizations and individuals. Feature selection is a …
Machine learning application to predict yields of solid products from biomass torrefaction
T Onsree, N Tippayawong - Renewable Energy, 2021 - Elsevier
Abstract Machine learning was used to develop a model that had the capability to predict
yields of solid products from biomass torrefaction using input features of biomass properties …
yields of solid products from biomass torrefaction using input features of biomass properties …
Microarray medical data classification using kernel ridge regression and modified cat swarm optimization based gene selection system
Microarray gene expression based medical data classification has remained as one of the
most challenging research areas in the field of bioinformatics, machine learning and pattern …
most challenging research areas in the field of bioinformatics, machine learning and pattern …
Adaptive genetic algorithms used to analyze behavior of complex system
AV Mokshin, VV Mokshin, LM Sharnin - Communications in Nonlinear …, 2019 - Elsevier
In the present study, we consider a complex system whose behavior is characterized by set
of various time-dependent factors. Some of these factors can characterize the external …
of various time-dependent factors. Some of these factors can characterize the external …
Correlation based feature selection algorithm for machine learning
N Gopika, AMK ME - 2018 3rd international conference on …, 2018 - ieeexplore.ieee.org
Feature selection is an effective strategy to reduce dimensionality, remove irrelevant data
and increase learning accuracy. The curse of dimensionality of data poses a severe …
and increase learning accuracy. The curse of dimensionality of data poses a severe …